A relative wave exposure index for the coastal zone of the Scotian Shelf-Bay of Fundy Bioregion

• Main Authors: O'Brien, John M, Wong, Melisa C., Stanley, Ryan R.E.
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: figshare 2022
• Subjects: Marine Biology; 60205 Marine and Estuarine Ecology incl. Marine Ichthyology; FOS Biological sciences; Ecology; Oceanography; FOS Earth and related environmental sciences; 90903 Geospatial Information Systems; FOS Environmental engineering; Arctic; Nunavut; Norway; Christensen; Forbes; Dee; Isachsen; Muñoz; Erikstad; Longva; Climate change; Iqaluit
• Online Access: https://dx.doi.org/10.6084/m9.figshare.c.5433567; https://figshare.com/collections/A_relative_wave_exposure_index_for_the_coastal_zone_of_the_Scotian_Shelf-Bay_of_Fundy_Bioregion/5433567

Exposure to wind-driven waves forms a key physical gradient in coastal areas that influences both ecological communities and human activities in the nearshore. For example, gradients in wave exposure are associated with patterns of diversity, abundance, and distribution of invertebrate communities along rocky shores (Norderhaug et al. 2012, Arribas et al. 2014). Exposure also influences important vegetated biogenic habitats such as seagrass and kelp beds through effects on primary productivity (Krumhansl & Scheibling 2011a, Krumhansl et al. 2021), resilience (Krumhansl et al. 2021), distribution and landscape patterns (Fonseca & Bell 1998, Bekkby et al. 2008), detrital export (Krumhansl & Scheibling 2011a), and rates of herbivory (Krumhansl & Scheibling 2011b, Frey & Gagnon 2015). Spatial variation and changes in the wave environment also impact human use of the coastal zone. For example, exposure factors into siting of ocean-based aquaculture operations (Lader et al. 2017) and decisions related to the development and adaptation of coastal infrastructure in the face of a changing climate (Hatcher & Forbes 2015). Therefore, the availability of wave exposure indices with regional coverage at a relatively high spatial resolution is required to support ecological modelling as well as marine spatial planning that guide the conservation and use of coastal ocean resources. We developed a spatial layer (35-m resolution) that provides a relative exposure index (REI) to wind-driven waves covering the entire coastal zone of the Canadian Scotian Shelf-Bay of Fundy Bioregion within 5 km from shore and the 50-m depth contour. REI is a fetch-derived index based on methods described in Keddy (1982) and Fonseca & Bell (1998). Our index combines calculations of fetch from 32 compass headings with modelled wind data (ERA5 reanalysis product) from the Copernicus Climate Data Store (Hersbach et al. 2018). Fetch is the unimpeded distance over which wind-driven waves can build (Shore Protection Manual 1975), and measured here as the distance (m) from a point in the ocean to land along a given heading. The resulting index is scaled between 0 (most protected) and 1 (most exposed). Here we provide the REI layer in raster format and a link to the source R and Python code developed to calculate fetch, download, summarize, and interpolate the modelled wind data, compute REI for input point features in an evenly spaced fishnet grid, and convert points to raster. References Arribas LP, Donnarumma L, Palomo MG, Scrosati RA (2014) Intertidal mussels as ecosystem engineers: Their associated invertebrate biodiversity under contrasting wave exposures. Mar Biodivers 44:203–211. Bekkby T, Rinde E, Erikstad L, Bakkestuen V, Longva O, Christensen O, Isæus M, Isachsen PE (2008) Spatial probability modelling of eelgrass (Zostera marina) distribution on the west coast of Norway. ICES J Mar Sci 65:1093–1101. Fonseca MS, Bell SS (1998) Influence of physical setting on seagrass landscapes. Mar Ecol Prog Ser 171:109–121. Frey DL, Gagnon P (2015) Thermal and Hydrodynamic Environments Mediate Individual and Aggregative Feeding of a Functionally Important Omnivore in Reef Communities. PLoS One 10:1–28. Hatcher S V., Forbes DL (2015) Exposure to coastal hazards in a rapidly expanding northern urban centre, Iqaluit, Nunavut. Arctic 68:453–471. Hersbach H, Bell B, Berrisford P, Biavati G, Horányi A, Muñoz Sabater J, Nicolas J, Peubey C, Radu R, Rozum I, Schepers D, Simmons A, Soci C, Dee D, Thépaut J-N (2018): ERA5 hourly data on pressure levels from 1979 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). (Accessed on 23-07-2021), 10.24381/cds.bd0915c6 Keddy PA (1982) Quantifying within-lake gradients of wave energy: interrelationships of wave energy, substrate particle size and shoreline plants in Axe Lake, Ontario. Aquat Biol 14:41–58. Krumhansl KA, Dowd M, Wong MC (2021) Multiple Metrics of Temperature, Light, and Water Motion Drive Gradients in Eelgrass Productivity and Resilience. Front Mar Sci 8:1–20. Krumhansl KA, Scheibling RE (2011a) Detrital production in Nova Scotian kelp beds: patterns and processes. Mar Ecol Prog Ser 421:67–82. Krumhansl KA, Scheibling RE (2011b) Spatial and temporal variation in grazing damage by the gastropod Lacuna vincta in Nova Scotian kelp beds. Aquat Biol 13:163–173. Lader P, Kristiansen D, Alver M, Bjelland HV, Myrhaug D (2017) Classification of aquaculture locations in Norway with respect to wind wave exposure. In Proceedings of the ASME 2017 36th International Conference on Ocean, Offshore and Arctic Engineering, Trondheim, Norway. Norderhaug KM, Christie H, Andersen GS, Bekkby T (2012) Does the diversity of kelp forest macrofauna increase with wave exposure? J Sea Res 69:36–42. Shore Protection Manual vol. 1. 1975. Fort Belvoir: US Army Coastal Engineering Research Center.